Text mining is a data analysis technique for, from an input of text data written in a natural language, such as texts in a free comment field in a questionnaire, grasping overall trends of their contents and finding useful knowledge. For example, in a call center, this makes it possible to grasp contents in an inquiry from an answering note, or find problems or improvements for a product from a questionnaire about the product.
For example, PTL 1 is for extracting a syntactic dependency relationship between two or more words, summing up a frequency of appearances of syntactic dependencies, arranging words into predefined categories, and thereafter, displaying a network of syntactic dependency relationships of words (FIGS. 8, 10 and 12 in PTL 1). For example, categories may include the part of speech of words or the function in a sentence, such as a subject and an object. Moreover, in displaying the aforementioned network, display conditions regarding the category, word, and syntactic dependency relationship may be adjusted to achieve analysis at one's discretion from a wide-range overview to refined details of syntactic dependency relationships.